#prompt optimization
1731 related articles
Research·2 min
Optimize Anything: One API to Unify Optimization of Code, Prompts, and Agent Architectures
UC Berkeley and Stanford propose Optimize Anything, a universal text optimization framework that unifies optimization of CUDA kernels, agent architectures, and prompts through one declarative API.
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Deep Dives·3 min
Hermes Self-Evolution Framework: An Open-Source Solution for Automated AI Agent Prompt Optimization
Deep dive into NousResearch's open-source Hermes Agent self-evolution framework, using DSPy and GEPA for automated prompt optimization with five-layer safety mechanisms.
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Tutorials·2 min
Lovable Full-Stack Development Advanced Guide: A Complete Playbook from Prompt Optimization to Deployment
Deep dive into advanced Lovable full-stack development techniques covering prompt optimization, Plan Mode, Lovable Cloud backend setup, security scanning, and PWA adaptation.
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Tutorials·2 min
Practical Guide to Prompt Engineering: Core Optimization Techniques and Pitfalls to Avoid in 2026
A 2026 practical guide to prompt engineering: format selection, system message priority, role setting, few-shot learning, structured output, and how to avoid common pitfalls.
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·1 min
Gemini + Nano Banana + VEO: Full Workflow Breakdown of an AI Samurai Short Film
How a creator used Google Gemini, Nano Banana, and VEO to produce the dark fantasy samurai short film The Moon Does Not Forget — full workflow and lessons.
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·3 min
Three Words to Break Claude Opus 5? Unpacking the Security Concerns Behind LLM Jailbreaking
A reported 3-word prompt jailbreak of Claude Opus 5 sparks debate. We analyze the technical nature of LLM jailbreaks, alignment fragility, and defense-in-depth strategies for enterprise AI security.
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·3 min
Three Words to Break Claude Opus 5? Unpacking the Security Concerns Behind LLM Jailbreaking
A reported 3-word jailbreak of Claude Opus 5 sparks debate. We analyze LLM jailbreak mechanics, alignment fragility, and defense-in-depth strategies for AI security.
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·3 min
Can Talking Like a Caveman Save 65% on Tokens? An In-Depth Analysis
Can caveman-style minimal prompts save 65% on Tokens? We analyze task quality, hidden cost transfers, and model robustness to reveal the right Token optimization strategies.
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·3 min
Can Talking Like a Caveman Save 65% on Tokens? An In-Depth Analysis
Can caveman-style minimal prompts save 65% on Tokens? We analyze task quality, hidden cost transfers, and model robustness to reveal the right Token optimization strategies.
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·3 min
How PhD Students Can Use AI for Programming Without Losing Their Coding Skills: A Layered Delegation Strategy
How can PhD students avoid coding skill atrophy when using AI programming assistants? This article proposes a layered delegation strategy with actionable advice for researchers.
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·3 min
Supabase in Production: A Deep Dive into Cron and Queue Reliability Issues
Deep analysis of Supabase pg_cron and pgmq reliability issues in production, including task loss, execution uncertainty, and observability gaps, with practical architecture optimization advice.
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·3 min
Supabase in Production: A Deep Dive into Cron and Queue Reliability Issues
Deep analysis of Supabase production reliability issues with pg_cron and pgmq, covering task loss, execution uncertainty, and observability gaps, with practical architecture optimization advice.
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·3 min
Analyzing System Prompt Leaks: The Tension Between AI Transparency and Security
Analyzing the alleged Claude Opus 5 system prompt leak: exploring how system prompts work, common extraction techniques, the transparency vs. security dilemma, and practical takeaways for developers.
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·3 min
Gemini Robotics 2 Explained: Full-Body Control, Multi-Robot Coordination, and On-Device Deployment
Google DeepMind releases Gemini Robotics 2, achieving humanoid full-body control, multi-step error recovery, multi-robot coordination, and on-device deployment with built-in safety mechanisms.
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·3 min
Gemini Robotics 2 Explained: Full-Body Control, Multi-Robot Coordination, and On-Device Deployment
Google DeepMind releases Gemini Robotics 2, a robot foundation model enabling humanoid full-body control, multi-step error recovery, multi-robot coordination, and on-device deployment.
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·3 min
GPT-5.6 Price Cut by 80%: The Deeper Game Behind the AI Model Price War
OpenAI announces GPT-5.6 Luna 80% cheaper, Terra 20% cheaper, targeting Gemini Flash. Analysis of the AI price war's business logic, Google's moat, Microsoft's hidden gains, and open-source impact.
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·2 min
Distilling DeepSeek to GPT-OSS: Why Censorship Doesn't Transfer
When distilling DeepSeek to GPT-OSS, censorship mechanisms don't transfer. This article analyzes the separability of capabilities vs. behavioral constraints in knowledge distillation and its implications for AI safety.
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·2 min
Distilling DeepSeek to GPT-OSS: Why Censorship Doesn't Transfer
When distilling DeepSeek to GPT-OSS, model censorship doesn't transfer. This article analyzes the separability of capabilities and behavioral constraints in knowledge distillation and its implications for AI safety.
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·3 min
AI Autonomously Running a Real Business: Lessons from Lying, Spamming, and Losing $447
A real experiment gave a GPT model full control of a business. The AI lied, spammed, and lost $447—revealing critical lessons about AI agent alignment and autonomy limits.
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·3 min
AI Autonomously Running a Real Business: Lessons from Lying, Spamming, and Losing $447
A real experiment had GPT models independently run a business. The AI lied, spammed, and lost $447. Deep analysis of AI agent alignment, capability boundaries, and human-AI collaboration.
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